// Copyright (c) 2017, The OctNet authors
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#ifndef OCTREE_RELU_CPU_H
#define OCTREE_RELU_CPU_H

#include "octnet/core/core.h"

extern "C" {

/// Computes the point-wise non-linearity y = max(0,x).
/// @param in  
/// @param inplace indicates if non-linearity should be computed in place,
///                in points to the same memory as out
/// @param out 
void octree_relu_cpu(const octree* in, bool inplace, octree* out);

/// Computes the point-wise gradient of y = max(0,x)
/// @param in 
/// @param grad_out
/// @param inplace indicates if non-linearity should be computed in place,
///                in points to the same memory as out
/// @param grad_in
void octree_relu_bwd_cpu(const octree* in, const octree* grad_out, bool inplace, octree* grad_in);


/// Computes the point-wise non-linearity y = 1 / (1 + exp(-x)).
/// @param in  
/// @param inplace indicates if non-linearity should be computed in place,
///                in points to the same memory as out
/// @param out 
void octree_sigmoid_cpu(const octree* in, bool inplace, octree* out);

/// Computes the point-wise gradient ofy = 1 / (1 + exp(-x)) 
/// @param in 
/// @param grad_out
/// @param inplace indicates if non-linearity should be computed in place,
///                in points to the same memory as out
/// @param grad_in
void octree_sigmoid_bwd_cpu(const octree* in, const octree* out, const octree* grad_out, bool inplace, octree* grad_in);


/// Computes the log-softmax y = log(exp(x) / sum_c exp(x_c)) over the feature channels
/// @param in
/// @param out
void octree_logsoftmax_cpu(const octree* in, octree* out);

/// Computes the gradient of log-softmax y = log(exp(x) / sum_c exp(x_c)) over 
/// the feature channels
/// @param in
/// @param out
void octree_logsoftmax_bwd_cpu(const octree* in, const octree* out, const octree* grad_out, octree* grad_in);
}

#endif 
